Econometrics Solutions

Added on - 18 Dec 2019

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Econometric
Table of Contentsa. Estimating the unknown parameters of the demand function..................................................3b. Interpret the regression coefficients when emergency room expect more calls......................3c. Testing the joint significance of Full moon and New moon at 5% significance level............6d. Autocorrelation test by using Durbin Watson model..............................................................6e.Re-estimating the model after correcting for autocorrelation................................................10QUESTION 2................................................................................................................................10a. Estimating supply equation by least square method..............................................................10b. Using Hausman to test to examine this belief at 5% level of significance............................12c. Estimating supply equation using an instrumental variables estimator with all availableinstruments.................................................................................................................................12QUESTION 3................................................................................................................................12a. Estimating a probit model with outcome...............................................................................12b. Using logit model with outcome variable..............................................................................17
a. Estimating the unknown parameters of the demand functionDemand function is highly significant which in turn assists in evaluating the impact theimpact of price of demand level. Hence, by making assessment it has been identified thatdemand for chicken is moderately affected from income level. This aspect can be supportedthrough the outcome of SPSS which presents that demand display of chicken is one of the mainfactors that have high level of impact on the demand of individuals.b. Interpret the regression coefficients when emergency room expect more callsIn the case of full moonRegressionVariables Entered/RemovedaModelVariablesEnteredVariablesRemovedMethod1fullmoonb.Entera. Dependent Variable: casesb. All requested variables entered.Model SummaryModelRR SquareAdjusted RSquareStd. Error of theEstimate1.027a.001-.00412.017a. Predictors: (Constant), fullmoonANOVAaModelSum of SquaresdfMean SquareFSig.1Regression23.461123.461.162.687bResidual32778.740227144.400
Total32802.201228a. Dependent Variable: casesb. Predictors: (Constant), fullmoonCoefficientsaModelUnstandardized CoefficientsStandardizedCoefficientstSig.BStd. ErrorBeta1(Constant)100.507.808124.339.000fullmoon1.7434.325.027.403.687a. Dependent Variable: casesInterpretation and analysis: The above depicted table shows that R and R square is0.0.2 and .001. This aspect shows that highly lower correlation takes placebetween the two factors such as emergency case and full moon condition. Outcomeof R square also clearly entails that if changes take place in one factor does nothave high level of impact on another. Along with this, level of significance is .69which shows that null hypothesis is rejected. On the basis of this aspect it can bestated that condition of full moon does not have significant impact on the numberof emergency cases.In the case of New moonRegressionVariables Entered/RemovedaModelVariablesEnteredVariablesRemovedMethod1newmoonb.Enter
a. Dependent Variable: casesb. All requested variables entered.Model SummaryModelRR SquareAdjusted RSquareStd. Error of theEstimate1.066a.004.00011.995a. Predictors: (Constant), newmoonANOVAaModelSum of SquaresdfMean SquareFSig.1Regression141.8541141.854.986.322bResidual32660.347227143.878Total32802.201228a. Dependent Variable: casesb. Predictors: (Constant), newmoonCoefficientsaModelUnstandardized CoefficientsStandardizedCoefficientstSig.BStd. ErrorBeta1(Constant)100.428.805124.748.000newmoon4.5724.605.066.993.322a. Dependent Variable: casesInterpretation and analysis: By applying the tool of SPSS it has been identified that R and Rsquare is .06 & .00. Such outcome clearly presents that both the aspect new moon and frequencyof emergency cases are not highly associated with each other. Along with this, significance levelis greater than standard limit which in turn entails that null hypothesis is accepted and other oneis rejected.
c. Testing the joint significance of Full moon and New moon at 5% significance levelJoint significance of full and new moonF-Test Two-Sample forVariancesFullmoonNewmoonMean0.034930.03057Variance0.033860.02976Observations229229df228228F1.13771P(F<=f) one-tail0.16536F Critical one-tail1.24399The above table presents that value of significance is 0.16 which in turn shows that nullhypothesis is accepted. Hence, by considering this, it can be stated that there is no high level ofassociation takes place between full and new moon.d. Autocorrelation test by using Durbin Watson modelRegressionVariables Entered/RemovedaModelVariablesEnteredVariablesRemovedMethod1newmoon,fullmoonb.Entera. Dependent Variable: casesb. All requested variables entered.Model Summaryb